فهرست مطالب
Frontmatter
Invited Presentations
Random Multivariate Search Trees
On Learning and Logic
Predictions as Statements and Decisions
Clustering, Un-, and Semisupervised Learning
A Sober Look at Clustering Stability
PAC Learning Axis-Aligned Mixtures of Gaussians with No Separation Assumption
Stable Transductive Learning
Uniform Convergence of Adaptive Graph-Based Regularization
Statistical Learning Theory
The Rademacher Complexity of Linear Transformation Classes
Function Classes That Approximate the Bayes Risk
Functional Classification with Margin Conditions
Significance and Recovery of Block Structures in Binary Matrices with Noise
Regularized Learning and Kernel Methods
Maximum Entropy Distribution Estimation with Generalized Regularization
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Mercer\'s Theorem, Feature Maps, and Smoothing
Learning Bounds for Support Vector Machines with Learned Kernels
Query Learning and Teaching
On Optimal Learning Algorithms for Multiplicity Automata
Exact Learning Composed Classes with a Small Number of Mistakes
DNF Are Teachable in the Average Case
Teaching Randomized Learners
Inductive Inference
Memory-Limited U-Shaped Learning
On Learning Languages from Positive Data and a Limited Number of Short Counterexamples
Learning Rational Stochastic Languages
Parent Assignment Is Hard for the MDL, AIC, and NML Costs
Learning Algorithms and Limitations on Learning
Uniform-Distribution Learnability of Noisy Linear Threshold Functions with Restricted Focus of Attention
Discriminative Learning Can Succeed Where Generative Learning Fails
Improved Lower Bounds for Learning Intersections of Halfspaces
Efficient Learning Algorithms Yield Circuit Lower Bounds
Online Aggregation
Optimal Oracle Inequality for Aggregation of Classifiers Under Low Noise Condition
Aggregation and Sparsity Via $\\ell$1 Penalized Least Squares
A Randomized Online Learning Algorithm for Better Variance Control
Online Prediction and Reinforcement Learning I
Online Learning with Variable Stage Duration
Online Learning Meets Optimization in the Dual
Online Tracking of Linear Subspaces
Online Multitask Learning
Online Prediction and Reinforcement Learning II
The Shortest Path Problem Under Partial Monitoring
Tracking the Best Hyperplane with a Simple Budget Perceptron
Logarithmic Regret Algorithms for Online Convex Optimization
Online Variance Minimization
Online Prediction and Reinforcement Learning III
Online Learning with Constraints
Continuous Experts and the Binning Algorithm
Competing with Wild Prediction Rules
Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path
Other Approaches
Ranking with a P-Norm Push
Subset Ranking Using Regression
Active Sampling for Multiple Output Identification
Improving Random Projections Using Marginal Information
Open Problems
Efficient Algorithms for General Active Learning
Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints
Backmatter
Invited Presentations
Random Multivariate Search Trees
On Learning and Logic
Predictions as Statements and Decisions
Clustering, Un-, and Semisupervised Learning
A Sober Look at Clustering Stability
PAC Learning Axis-Aligned Mixtures of Gaussians with No Separation Assumption
Stable Transductive Learning
Uniform Convergence of Adaptive Graph-Based Regularization
Statistical Learning Theory
The Rademacher Complexity of Linear Transformation Classes
Function Classes That Approximate the Bayes Risk
Functional Classification with Margin Conditions
Significance and Recovery of Block Structures in Binary Matrices with Noise
Regularized Learning and Kernel Methods
Maximum Entropy Distribution Estimation with Generalized Regularization
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Mercer\'s Theorem, Feature Maps, and Smoothing
Learning Bounds for Support Vector Machines with Learned Kernels
Query Learning and Teaching
On Optimal Learning Algorithms for Multiplicity Automata
Exact Learning Composed Classes with a Small Number of Mistakes
DNF Are Teachable in the Average Case
Teaching Randomized Learners
Inductive Inference
Memory-Limited U-Shaped Learning
On Learning Languages from Positive Data and a Limited Number of Short Counterexamples
Learning Rational Stochastic Languages
Parent Assignment Is Hard for the MDL, AIC, and NML Costs
Learning Algorithms and Limitations on Learning
Uniform-Distribution Learnability of Noisy Linear Threshold Functions with Restricted Focus of Attention
Discriminative Learning Can Succeed Where Generative Learning Fails
Improved Lower Bounds for Learning Intersections of Halfspaces
Efficient Learning Algorithms Yield Circuit Lower Bounds
Online Aggregation
Optimal Oracle Inequality for Aggregation of Classifiers Under Low Noise Condition
Aggregation and Sparsity Via $\\ell$
A Randomized Online Learning Algorithm for Better Variance Control
Online Prediction and Reinforcement Learning I
Online Learning with Variable Stage Duration
Online Learning Meets Optimization in the Dual
Online Tracking of Linear Subspaces
Online Multitask Learning
Online Prediction and Reinforcement Learning II
The Shortest Path Problem Under Partial Monitoring
Tracking the Best Hyperplane with a Simple Budget Perceptron
Logarithmic Regret Algorithms for Online Convex Optimization
Online Variance Minimization
Online Prediction and Reinforcement Learning III
Online Learning with Constraints
Continuous Experts and the Binning Algorithm
Competing with Wild Prediction Rules
Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path
Other Approaches
Ranking with a P-Norm Push
Subset Ranking Using Regression
Active Sampling for Multiple Output Identification
Improving Random Projections Using Marginal Information
Open Problems
Efficient Algorithms for General Active Learning
Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints
Backmatter
